Fine mapping without phenotyping: Identification of selection targets in secondary Evolve and Resequence experiments

Abstract

Evolve and Resequence (E&R) studies investigate the genomic selection response of populations in an Experimental Evolution setup. Despite the popularity of E&R, empirical studies in sexually reproducing organisms typically suffer from an excess of candidate loci due to linkage disequilibrium, and single gene or SNP resolution is the exception rather than the rule. Recently, so-called "secondary E&R" has been suggested as promising experimental follow-up procedure to confirm putatively selected regions from a primary E&R study. Secondary E&R provides also the opportunity to increase mapping resolution by allowing for additional recombination events, which separate the selection target from neutral hitchhikers. Here, we use computer simulations to assess the effect of different crossing schemes, population size, experimental duration, and number of replicates on the power and resolution of secondary E&R. We find that the crossing scheme and population size are crucial factors determining power and resolution of secondary E&R: a simple crossing scheme with few founder lines consistently outcompetes crossing schemes where evolved populations from a primary E&R experiment are mixed with a complex ancestral founder population. Regardless of the experimental design tested, a population size of at least 4,800 individuals, which is roughly 5 times larger than population sizes in typical E&R studies, is required to achieve a power of at least 75%. Our study provides an important step towards improved experimental designs aiming to characterize causative SNPs in Experimental Evolution studies. SignificanceDespite the popularity of Evolve and Resequence (E&R) to investigate genomic selection responses, most studies that use sexually reproducing organisms have broad selection signatures and an excess of candidate loci due to linkage disequilibrium. In this study, we use computer simulations and statistical modelling to evaluate the effects of different experimental and population genetic parameters on the success of potential follow-up experiments (=secondary E&R) aiming to validate and fine-map selection signatures of primary studies. We found that a large population size in combination with a simple crossing scheme is key to the success of secondary E&R in Drosophila.